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How a Data Analytics strategy supports resiliency in uncertain times?

As the organizations work to recuperate from the uncertainties and far-reaching implications of the COVID-19 pandemic, it’s important to ascertain that businesses are resilient and can acclimate expeditiously to mutable conditions. One way to engender resilience is to connect data to decisions by engendering a data analytics strategy that limpidly links people, processes, technologies, and data. Think of the analytics strategy as your north star – and your data strategy as the fortifying framework.


How an Analytics strategy works:

An analytics strategy is designed to ameliorate all the ways organizations design, deploy, monitor, and govern analytics. It establishes the infrastructure, plumbing, processes, and people needed to distribute the right analytics at the right time across an organization.  Organization analytics strategy should answer key questions cognate to:

  • Business goals that analytics can apprise.
  • Quantifications that will show you’ve achieved the goals.
  • Data that are available (or could be available) to fortify analytics.
  • Infrastructure, or the multifaceted components needed to achieve your desired results.
  • Insights, which involves determining how, when, and where to deploy your insights to fortify decision processes.

Organizations can benefit from a data analytics strategy in four main ways.

  • Teams can stay fixated on high-value activities that lead to business results because you’ll have analytic models that are pellucidly aligned with concrete business issues.
  • Organizations won’t have to rework or discard models because you’ll ken what it takes to deploy models into your decision processes.
  • Organizations can retrain or supersede models expeditiously, so they’ll perpetuate to perform because you’ll employ mechanisms to govern and monitor your analytics. You’ll additionally ken when models have outlived their usefulness and need to be retired.
  • Organizations can fixate on high-value business decisions that demonstrate ROI from analytics initiatives because you've defined key metrics to capture the business impact.

How a data strategy support analytics to create resilience

A data strategy is a foundation for engendering resilient analytic processes for your organization. The data strategy is vital because analytics relies on data for decision processes. The goal of the data strategy is to define how data is acquired, stored, managed, shared, and utilized for analytics and decision making. Cerebrate of the data strategy as your road map for ascertaining the right data is in the right place, at the right time.

The data strategy needs to address details around how data will fortify the analytics strategy. This type of strategy ascertains that data will be identified, stored, and provisioned in a way that both analytic and business communities can readily understand and use to expedite analytic and decision processes.

The data must be integrated in a consistent and cohesive way that adheres to governance policies and procedures. And the policies, procedures, data definitions, and lineage circumventing the data should be transparent to data and analytics users. In turn, they’ll ken that the correct data is being utilized in analytics to fortify data-driven decisions.

A solid data strategy builds trust because it ascertains that the data being utilized for analytics is fit for its purport. It builds confidence because it defines criteria for ascertaining the data can be facilely expounded and is transparent, defendable, and justifiable for the business processes in which it’s utilized.

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